Title :
A case study on the application of instance selection techniques for Genetic Fuzzy Rule-Based Classifiers
Author :
Giglio, Bruno ; Marcelloni, Francesco ; Fazzolari, Michela ; Alcalá, Rafael ; Herrera, Francisco
Author_Institution :
Dipt. di Ing. dell´´Inf., Elettron., Inf., Telecomun., Univ. of Pisa, Pisa, Italy
Abstract :
When considering data sets characterized by a large number of instances, the computational time required to apply Genetic Algorithms for generating Fuzzy Rule-Based Classifiers increases considerably, mainly due to the fitness evaluation. Another important problem associated to these kinds of data sets is an undesired increase of the obtained model complexity.
Keywords :
computational complexity; data mining; fuzzy set theory; genetic algorithms; learning (artificial intelligence); pattern classification; classification accuracy; computational time; evolutionary learning; fuzzy association rule-based classification model; genetic algorithms; genetic fuzzy rule-based classifiers; instance selection techniques; model complexity; Accuracy; Association rules; Biological cells; Genetic algorithms; Genetics; Itemsets; Training;
Conference_Titel :
Fuzzy Systems (FUZZ-IEEE), 2012 IEEE International Conference on
Conference_Location :
Brisbane, QLD
Print_ISBN :
978-1-4673-1507-4
Electronic_ISBN :
1098-7584
DOI :
10.1109/FUZZ-IEEE.2012.6251191
